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Econometrics (26:220: 507)
Statistical techniques for the analysis of models applicable to economic data and their application to management problems.



Financial Institutions & Markets (22:390:604)
Presents a detailed overview of the theory and institutional features of the U.S. financial system. Provides a comprehensive review of U.S. financial markets. Covers a survey of flow-of-funds data and U.S. financial markets and institutions, capital market theory, financial factors and economic activity, theory of the level and structure of interest rates. Prerequisites: 223:581 or 223:521; 223:591 or 223:520; and 390:587 or 390:522.



Financial Modeling I (22:839:571)
This course is the first of the two-course sequence in financial theory for Ph.D. and MQF students. The course surveys the fundamental assumptions and the analytical techniques of the modern finance theory. It builds a foundation for the study of higher-level courses in investment theory and corporate finance. Topics include capital market equilibrium models, risk analysis using utility theory, state preference theory, portfolio selection, market efficiency, and empirical tests of asset pricing models.



Financial Modeling II (22:839:662)
This course covers continuous time finance, similar to an advanced Ph.D. course in asset pricing.
It follows Financial Modeling I which covers discrete time finance and continues with continuous time financial theories. Topic-wise, it covers basic theories (backward and forward equations, change of measure, state pricing, arbitrage pricing, martingales), derivatives pricing (Black-Scholes model, Heston model, Geske model, Merton-Rabinovitch model), term structure of interest rates (Vasicek model, CIR model, HJM model, Hull-White model), multi-factor models (Chen-Scott model, Bakshi-Cao-Chen-Scott model, Duffie-Pan-Singleton model), credit derivatives (Jarrow-Turnbull model, Duffie-Singleton model) and some numerical methods (binomial model, finite difference methods, Monte-Carlo).
Interested students can get a good idea from the following books: Merton – Continuous Time Finance, Duffie - Dynamic Asset Pricing Theory, Ingersoll - Theory of Financial Decision Making, and similar others.



Fundamentals of Career Planning (22:135:583)
These seminars are designed to provide students with an overview of the services offered by the Office of Career Management (OCM). It will also introduce students to the Rutgers Business School’s Career Development Program (CDP), including a presentation focused on business etiquette essentials and a timeline of scheduled events.



Introduction to Finance (Course # TBD)
The course will focus on key concepts in Finance such as the time value of money, the relationship between risk and return, and asset pricing / valuation theories. In addition, some practical institutional knowledge will be discussed.




Introduction to Probability (26:960:575)
This course covers set theory, sample spaces, events, probability functions on sample spaces, combinatorial methods, conditional probability, Bayes' theorem, Markov chains (if time permits), random variables and distributions (discrete, continuous, mixed, multivariate), conditional distributions, functions of random variables, expectations (mean, variance, covariance, correlation, moments, conditional expectations), moment-generating functions, inequalities (Chebyshev, Jensen), limit theorems (laws of large numbers, central limit theorem), large sample approximations (Poisson and normal to binomial, normal to Poisson, normal to the t- distribution, etc.), special distributions (Bernoulli, binomial, multinomial, geometric, negative binomial, hypergeometric, Poisson, exponential, gamma, beta, t, normal and multivariate normal, and chi-square.



Investment Analysis & Management (22:390:603)
Provides overview of the fields of security analysis and portfolio management. Introduces the analysis of individual investments with special reference to common stock. Covers nature of financial markets, security pricing models, critiques of techniques of security analysis. Introduces problems of portfolio selection. Designed for the finance major who is interested in the security/investment area as a possible career.




Microeconomics (26:220:501)
These courses survey and apply consumer theory, theory of the firm, decision making under uncertainty, elements of marginal analysis, risk analysis to problems in demand analysis, production, cost, market structure, pricing, and an introduction to non-cooperative game theory with applications to economic problems with asymmetric information.





Numerical Analysis (22:839:510)
This course derives, analyzes, and applies methods used to solve numerical problems with computers; solution of linear and nonlinear algebraic equations by iterations, linear equations and matrices, least squares, interpolation and approximation of functions, numerical differentiation and integration, and numerical solutions of ordinary differential equations.



Object Oriented Programming in Finance I (22:839:614) & II (22:839:615)
C++ is a higher level computer language with multiple personalities. The objective for this two part course is for the student to become proficient in C++ programming so as to be able to develop c++ functions and classes for independent and interrelated economic models via parametrization and/or class interrelation. Topics will include data structures from the simple data types and matrices to interrelated classes and inheritance; standard mathematics libraries, logic and processing from simple conditionals to iteration and multitasking and the various forms of parametrization.



Operations Research Models in Finance (26:711:685)
This course teaches students the use of Operations Research Models in the areas of Risk and Portfolio Management.



Options (22:390:609)
Introduces the rapidly developing markets in futures and options. Subjects include the nature of such markets, the pricing of instruments in the markets, and the use of such instruments by both speculators and hedgers.



Elective CoursesThe descriptions below briefly outline some of the elective courses.



Advanced Econometrics (26:223:655)
Simultaneous equation models, seemingly unrelated regressions, autocorrelation, ARIMA models, and nonlinear estimation. Applications of such techniques to theoretical and empirical problems.

Advanced Financial Management (22:390:605)
Examines the problems faced by the corporate financial manager on the theoretical, analytical, and applied level. The impact of the financing decision upon the value of the firm is analyzed. Theoretical and analytical aspects of the capital budgeting decision. An analytical framework is presented to evaluate leasing, bond refunding, and mergers and acquisitions. Theories of corporate governance are discussed.



Analysis of Fixed Income Securities (22:390:611)
This course is designed to explore the investment characteristics, pricing, and risk/reward potential of fixed income securities. The securities covered include bonds---with and without embedded options, mortgages and mortgage-backed securities together with their derivatives such as collateralized mortgage obligations (CMO's), income-only (I0's) and principal-only (PO's) strips, interest rate swaps, and interest rate futures and option contracts. In addition this course will explore the strategies for investing in portfolios of fixed income securities. Prerequisites: 390:587 or 390:522; and 390:603.



Applied Portfolio Management (22:390:658)
This course teaches students how to create and manage on a continuing basis and actual portfolio that meets the needs of a client. At most, seven students will be accepted to this course.



Credit Derivatives (16:642:611)
In addition to equity, interest rates, FX, and commodity derivatives, credit derivatives play an increasingly important role in financial markets. The course will include a review of jump processes; the basic theory of single name credit derivative modeling; structual, reduced form or intensity models; credit default swaps; default correlation, multiname credit derivative modeling; top down versus bottom up models; basket credit derivatives; collaterized debt obligations; and tranche options. The goal of the course is to cover most of the material in "Credit Risk Modeling" by David Lando (Princeton University Press, 2004) or "Credit Derivatives Pricing Models" by Philipp Schonbucher (Wiley, 2004).



Empirical Finance (26:390:668)
The application of econometric techniques to the empirical study of finance and financial economics, especially the examination of weak effects with very large samples. Among the topics examined are measurement problems in event studies, the effects of anomalies in reported prices on computed returns, and how to deal with those effects. After completing this course and Advanced Econometrics, the student should be able to evaluate critically both proposed and published studies and will become adept at designing his or her own studies.




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